ROI-based DTI analysis

Preparation

Loading the data set and the libraries

options(width=108)
out=F
library(xlsx)

## Loading required package: rJava

## Loading required package: xlsxjars

library(ggplot2)
library(plyr)
# '../' is only necessary on Windows
projDir <- paste(path.expand('~'), 'Dropbox/Projects/md/dti/', sep='/')
wmLabels <- read.xlsx(file=paste(projDir, 'analyses/wmLabels.xlsx', sep=''), 1)

Subsetting to the ROI list 1 (CC & CR)

# Corpus callosum and corona radiata:
ds <- read.csv(paste(projDir, 'analyses/roiDS.csv', sep=''))
roiList1 <- c(3:5,24,26,28,23,25,27)
ds1 <- ds[ds$labelID %in% roiList1,]

Plots

FA

sumds1 <- ddply(ds1, c('group','run','Abbrev','labelID','Label'), summarise, 
                meanFA=mean(value))
head(sumds1)

##   group run  Abbrev labelID                      Label    meanFA
## 1   HEP   1  antCRL      24  Anterior corona radiata L 0.1076521
## 2   HEP   1  antCRR      23  Anterior corona radiata R 0.1042210
## 3   HEP   1     bCC       4    Body of corpus callosum 0.1643308
## 4   HEP   1     gCC       3    Genu of corpus callosum 0.1402270
## 5   HEP   1 postCRL      28 Posterior corona radiata L 0.1073760
## 6   HEP   1 postCRR      27 Posterior corona radiata R 0.1185454

for(curRoi in roiList1){
    p = ggplot(sumds1[sumds1$labelID==curRoi,], aes(x=run, y=meanFA, color=group)) + 
        geom_point() + geom_line() + scale_x_continuous(breaks = 1:3) +
        labs(x='Time point', y='Mean FA value', color='Group',
             title=unique(sumds1[sumds1$labelID==curRoi, 'Label'])) + theme_bw()
    plot(p)
}

HEP group (control)

sumds1subj <- ddply(ds1, c('subjID', 'group','run','Abbrev','labelID','Label'), summarise, 
                meanFA=mean(value))
head(sumds1subj)

##   subjID group run  Abbrev labelID                      Label     meanFA
## 1 MCI001   HEP   1  antCRL      24  Anterior corona radiata L 0.10073517
## 2 MCI001   HEP   1  antCRR      23  Anterior corona radiata R 0.09970374
## 3 MCI001   HEP   1     bCC       4    Body of corpus callosum 0.16100824
## 4 MCI001   HEP   1     gCC       3    Genu of corpus callosum 0.14091434
## 5 MCI001   HEP   1 postCRL      28 Posterior corona radiata L 0.09954849
## 6 MCI001   HEP   1 postCRR      27 Posterior corona radiata R 0.11165860

for(curRoi in roiList1){
    sumds1ss <- sumds1subj[sumds1subj$labelID==curRoi & sumds1subj$group=='HEP',]
    p = ggplot(sumds1ss, aes(x=run, y=meanFA, color=subjID)) + 
        geom_point() + geom_line() + scale_x_continuous(breaks = 1:3) +
        labs(x='Time point', y='Mean FA value', color='Participant',
             title=unique(sumds1[sumds1$labelID==curRoi, 'Label'])) + 
        theme_bw()
    plot(p)
}

MAP group (meditation)

for(curRoi in roiList1){
    sumds1ss <- sumds1subj[sumds1subj$labelID==curRoi & sumds1subj$group=='MAP',]
    p = ggplot(sumds1ss, aes(x=run, y=meanFA, color=subjID)) + 
        geom_point() + geom_line() + scale_x_continuous(breaks = 1:3) +
        labs(x='Time point', y='Mean FA value', color='Participant',
             title=unique(sumds1[sumds1$labelID==curRoi, 'Label'])) + 
        theme_bw()
    plot(p)
}

AD

dsad <- read.csv(paste(projDir, 'analyses/roiDS_AD.csv', sep=''))
dsad1 <- dsad[dsad$labelID %in% roiList1,]
sumdsad1 <- ddply(dsad1, c('group','run','Abbrev','labelID','Label'), summarise, 
                meanFA=mean(value))
head(sumdsad1)

##   group run  Abbrev labelID                      Label       meanFA
## 1   HEP   1  antCRL      24  Anterior corona radiata L 0.0002017303
## 2   HEP   1  antCRR      23  Anterior corona radiata R 0.0001951903
## 3   HEP   1     bCC       4    Body of corpus callosum 0.0002841522
## 4   HEP   1     gCC       3    Genu of corpus callosum 0.0002406790
## 5   HEP   1 postCRL      28 Posterior corona radiata L 0.0001909010
## 6   HEP   1 postCRR      27 Posterior corona radiata R 0.0002075941

for(curRoi in roiList1){
    p = ggplot(sumdsad1[sumdsad1$labelID==curRoi,], aes(x=run, y=meanFA, color=group)) + 
        geom_point() + geom_line() + scale_x_continuous(breaks = 1:3) +
        labs(x='Time point', y='Mean AD value', color='Group',
             title=unique(sumdsad1[sumdsad1$labelID==curRoi, 'Label'])) + theme_bw()
    plot(p)
}

RD

dsrd <- read.csv(paste(projDir, 'analyses/roiDS_RD.csv', sep=''))
dsrd1 <- dsrd[dsrd$labelID %in% roiList1,]
sumdsrd1 <- ddply(dsrd1, c('group','run','Abbrev','labelID','Label'), summarise, 
                meanFA=mean(value))
head(sumdsrd1)

##   group run  Abbrev labelID                      Label       meanFA
## 1   HEP   1  antCRL      24  Anterior corona radiata L 9.320773e-05
## 2   HEP   1  antCRR      23  Anterior corona radiata R 8.920448e-05
## 3   HEP   1     bCC       4    Body of corpus callosum 7.258213e-05
## 4   HEP   1     gCC       3    Genu of corpus callosum 6.145534e-05
## 5   HEP   1 postCRL      28 Posterior corona radiata L 8.088740e-05
## 6   HEP   1 postCRR      27 Posterior corona radiata R 8.490367e-05

for(curRoi in roiList1){
    p = ggplot(sumdsrd1[sumdsrd1$labelID==curRoi,], aes(x=run, y=meanFA, color=group)) + 
        geom_point() + geom_line() + scale_x_continuous(breaks = 1:3) +
        labs(x='Time point', y='Mean RD value', color='Group',
             title=unique(sumdsrd1[sumdsrd1$labelID==curRoi, 'Label'])) + theme_bw()
    plot(p)
}

Age

FA

dsr1 <- read.csv(paste(projDir, 'analyses/roiRun1_FA.csv', sep=''))
p <- ggplot(dsr1, aes(x=age, y=value)) + 
    geom_point() + stat_smooth(method='lm', alpha=.1) +
    labs(x='Age', y='FA value', title='FA & age') + theme_bw() + 
    theme(legend.position='none')
plot(p)

FA across structures

for(curRoi in unique(ds$Abbrev)){
    p <- ggplot(dsr1[dsr1$Abbrev==curRoi,], aes(x=age, y=value)) + 
        geom_point() + stat_smooth(method='lm') +
        labs(x='Age', y='FA value', title=curRoi) + theme_bw()
    plot(p)
}